a Of*@s&dZddlmZddlmZddlZddlmZm Z ddl m Z m Z m Z ddlmZddlmZdd lmZmZdd lmZdd lmZddlmmZdd lmZmZdd l m!Z!ddl"m#Z#erddl$m%Z%e#gdej&edde#gdeGddde!Z'dddddddddZ(dS)z implement the TimedeltaIndex ) annotations) TYPE_CHECKINGN)indexlib) Resolution Timedelta to_offset)disallow_ambiguous_unit)find_stack_level) is_scalar pandas_dtype) ABCSeries)TimedeltaArray)Indexmaybe_extract_name)DatetimeTimedeltaMixin) inherit_names)DtypeObj)__neg____pos____abs__ total_secondsroundfloorceilT)wrap) componentsZto_pytimedeltasumZstdZmedianc@seZdZUdZdZeZeddddZde d<e j Z ed dd d Z d e je je jd d d fddddZdddddZddZddddZddddZeddd d!Zd S)"TimedeltaIndexal Immutable Index of timedelta64 data. Represented internally as int64, and scalars returned Timedelta objects. Parameters ---------- data : array-like (1-dimensional), optional Optional timedelta-like data to construct index with. unit : {'D', 'h', 'm', 's', 'ms', 'us', 'ns'}, optional The unit of ``data``. .. deprecated:: 2.2.0 Use ``pd.to_timedelta`` instead. freq : str or pandas offset object, optional One of pandas date offset strings or corresponding objects. The string ``'infer'`` can be passed in order to set the frequency of the index as the inferred frequency upon creation. dtype : numpy.dtype or str, default None Valid ``numpy`` dtypes are ``timedelta64[ns]``, ``timedelta64[us]``, ``timedelta64[ms]``, and ``timedelta64[s]``. copy : bool Make a copy of input array. name : object Name to be stored in the index. Attributes ---------- days seconds microseconds nanoseconds components inferred_freq Methods ------- to_pytimedelta to_series round floor ceil to_frame mean See Also -------- Index : The base pandas Index type. Timedelta : Represents a duration between two dates or times. DatetimeIndex : Index of datetime64 data. PeriodIndex : Index of Period data. timedelta_range : Create a fixed-frequency TimedeltaIndex. Notes ----- To learn more about the frequency strings, please see `this link `__. Examples -------- >>> pd.TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days']) TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[ns]', freq=None) We can also let pandas infer the frequency when possible. >>> pd.TimedeltaIndex(np.arange(5) * 24 * 3600 * 1e9, freq='infer') TimedeltaIndex(['0 days', '1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[ns]', freq='D') Ztimedeltaindexztype[libindex.TimedeltaEngine])returncCstjSN)libindexZTimedeltaEngineselfr$W/var/www/ai-form-bot/venv/lib/python3.9/site-packages/pandas/core/indexes/timedeltas.py _engine_typeszTimedeltaIndex._engine_typer_datazResolution | NonecCs|jjSr )r'_resolution_objr"r$r$r%r(szTimedeltaIndex._resolution_objNFbool)copyc CsX|tjur&tjd|jdttd|tjurNtjd|jdttdnd}t|||}t|rp| |t ||durt |}t |t r|tjur|dus||jkr|r|}|j||dSt |tr|tjur|dur|dus||jkr|r |S|St j|||||d}d} |sHt |ttfrH|j} |j||| dS) NzThe 'closed' keyword in zD construction is deprecated and will be removed in a future version.) stacklevelzThe 'unit' keyword in za construction is deprecated and will be removed in a future version. Use pd.to_timedelta instead.name)frequnitdtyper*)r-refs)r no_defaultwarningswarn__name__ FutureWarningr rr Z_raise_scalar_data_errorr r isinstancerr0r* _simple_newrZ_viewZ_from_sequence_not_strictr rZ _references) clsdatar/r.closedr0r*r-tdarrr1r$r$r%__new__sd       zTimedeltaIndex.__new__r)r0rcCs t|dS)zF Can we compare values of the given dtype to our own? m)rZ is_np_dtype)r#r0r$r$r%_is_comparable_dtypesz#TimedeltaIndex._is_comparable_dtypec CsZ||z|jj|dd}Wn.tyL}zt||WYd}~n d}~00t||S)z Get integer location for requested label Returns ------- loc : int, slice, or ndarray[int] F)ZunboxN)Z_check_indexing_errorr'Z_validate_scalar TypeErrorKeyErrorrget_loc)r#keyerrr$r$r%rBs   zTimedeltaIndex.get_locstr)labelcCst|}|dfSr )r)r#rFparsedr$r$r%_parse_with_resoszTimedeltaIndex._parse_with_resor)rGcCs,||j}|t|jtdd}||fS)Nns)rZresolution_stringrr)r#ZresorGZlboundZrboundr$r$r%_parsed_string_to_boundss z'TimedeltaIndex._parsed_string_to_boundscCsdS)NZ timedelta64r$r"r$r$r% inferred_typeszTimedeltaIndex.inferred_type)r5 __module__ __qualname____doc__Z_typrZ _data_clspropertyr&__annotations__rZ_get_string_slicer(rr2r=r?rBrHrKrLr$r$r$r%r&s. HI r)r/z int | Nonez str | None)periodsr/rcCsF|durt|||rd}t|}tj||||||d}tj||dS)a$ Return a fixed frequency TimedeltaIndex with day as the default. Parameters ---------- start : str or timedelta-like, default None Left bound for generating timedeltas. end : str or timedelta-like, default None Right bound for generating timedeltas. periods : int, default None Number of periods to generate. freq : str, Timedelta, datetime.timedelta, or DateOffset, default 'D' Frequency strings can have multiples, e.g. '5h'. name : str, default None Name of the resulting TimedeltaIndex. closed : str, default None Make the interval closed with respect to the given frequency to the 'left', 'right', or both sides (None). unit : str, default None Specify the desired resolution of the result. .. versionadded:: 2.0.0 Returns ------- TimedeltaIndex Notes ----- Of the four parameters ``start``, ``end``, ``periods``, and ``freq``, exactly three must be specified. If ``freq`` is omitted, the resulting ``TimedeltaIndex`` will have ``periods`` linearly spaced elements between ``start`` and ``end`` (closed on both sides). To learn more about the frequency strings, please see `this link `__. Examples -------- >>> pd.timedelta_range(start='1 day', periods=4) TimedeltaIndex(['1 days', '2 days', '3 days', '4 days'], dtype='timedelta64[ns]', freq='D') The ``closed`` parameter specifies which endpoint is included. The default behavior is to include both endpoints. >>> pd.timedelta_range(start='1 day', periods=4, closed='right') TimedeltaIndex(['2 days', '3 days', '4 days'], dtype='timedelta64[ns]', freq='D') The ``freq`` parameter specifies the frequency of the TimedeltaIndex. Only fixed frequencies can be passed, non-fixed frequencies such as 'M' (month end) will raise. >>> pd.timedelta_range(start='1 day', end='2 days', freq='6h') TimedeltaIndex(['1 days 00:00:00', '1 days 06:00:00', '1 days 12:00:00', '1 days 18:00:00', '2 days 00:00:00'], dtype='timedelta64[ns]', freq='6h') Specify ``start``, ``end``, and ``periods``; the frequency is generated automatically (linearly spaced). >>> pd.timedelta_range(start='1 day', end='5 days', periods=4) TimedeltaIndex(['1 days 00:00:00', '2 days 08:00:00', '3 days 16:00:00', '5 days 00:00:00'], dtype='timedelta64[ns]', freq=None) **Specify a unit** >>> pd.timedelta_range("1 Day", periods=3, freq="100000D", unit="s") TimedeltaIndex(['1 days', '100001 days', '200001 days'], dtype='timedelta64[s]', freq='100000D') ND)r;r/r,)comZany_nonerrZ_generate_rangerr8)startendrRr.r-r;r/r<r$r$r%timedelta_range sS rW)NNNNNN))rO __future__rtypingrr3Z pandas._libsrr!rZpandas._libs.tslibsrrrZpandas._libs.tslibs.timedeltasr Zpandas.util._exceptionsr Zpandas.core.dtypes.commonr r Zpandas.core.dtypes.genericr Zpandas.core.arrays.timedeltasrZpandas.core.commoncorecommonrTZpandas.core.indexes.baserrZ pandas.core.indexes.datetimelikerZpandas.core.indexes.extensionrZpandas._typingrZ _field_opsrrWr$r$r$r%sL          V